Identifying Implicit Requirements in SRS Big Data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Over the past few years, we have worked on pioneering an approach that employs Commonsense Knowledge (CSK) to automate the identification of Implicit Requirements (IMRs) from text in large Software Requirements Specifications (SRS) documents. This paper builds on our IMR-identification approach by adding CNN-based deep learning to detect IMRs from complex SRS big data such as images and tables.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6169-6171
Number of pages3
ISBN (Electronic)9781728108582
DOIs
StatePublished - Dec 2019
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: 9 Dec 201912 Dec 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference2019 IEEE International Conference on Big Data, Big Data 2019
CountryUnited States
CityLos Angeles
Period9/12/1912/12/19

Keywords

  • Commonsense Knowledge
  • Domain Ontology
  • IMRs
  • Requirements Engineering
  • Text Mining

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  • Cite this

    Onyeka, E., Anu, V., & Varde, A. S. (2019). Identifying Implicit Requirements in SRS Big Data. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 6169-6171). [9006086] (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData47090.2019.9006086